A genetic approach to the scheduling of preventive maintenance tasks on a single product manufacturing production line

Abstract

The present article deals with optimising the schedule of maintenance tasks of all the machines in a single product manufacturing production line. This study was made in the context of one machine assigned to one operator. This operator intervenes to change tools during a stoppage. Our goal is to increase the overall through-put of the line. We firstly formalised the problem and showed the difficulty of its analytical resolution. Then, we presented the software environment that enables the resolution of this problem: it is made up of a simulator of the production line and an optimiser using the genetic algorithms. Our approach to the scheduling of maintenance tasks was validated upon an actual production line of car engines. We focused our study on the setting of parameters of a genetic algorithm. We proceeded with a systematic approach inspired by the Taguchi method to find the best combination of levels for each studied parameter and performed a statistical confirmation of the results. Finally we validated the genetic approach as against naive optimisation.